article Open access

Breast Cancer Analysis Using Machine Learning Algorithms

  • Journal of Intelligent Systems and Computing
Research footprint

At a glance

Citations
0
References
8
Comments
0
Paper overview

Abstract

Breast cancer (BC) is one of the most common types of cancer and one of the leading causes of death for women around the world. Breast cancer occurs when cells in the breast cells mutate and form a malignant tumor. State-of-the-art technologies can detect BC at an early stage, which helps in treatment and reduces the risk of death. Medical doctors commonly use breast tissue biopsy when diagnosing breast cancer, enabling them to take a microscopic look for breast tissue and determine whether the tissue is benign or malignant. To improve biopsy results, many researchers have studied the feasibility of using artificial intelligence (AI) to help doctors detect any harmful changes that may lead to cancer. In this research work detail analysis of Breast Cancer using support vector machine (SVM) and convolutional neural networks (CNN) algorithms is performed and the results show CNN has more superior results in comparison to SVM in the recognition of images affected by Breast Cancer.

Record transparency

Publication details

DOI
10.51682/jiscom.00201003.2021
OpenAlex
W3169689461
Document type
article
Language
EN
Source
Journal of Intelligent Systems and Computing
Last metadata update
Community

Comments

Log in to join the discussion.

  1. No comments yet. Start the discussion.